• International conference on construction engineering and project management
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• 2015.10a
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• pp.349-352
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• 2015

Size of building has a direct relationship with building cost, energy use and space maintenance cost. Therefore, minimizing building size during a project development is of paramount importance against such wastes. However, incautious reduction of building size may result in crowded space, and therefore harms the functionality despite the fact that building is supposed to satisfactorily support users' activity. A well-balanced design solution is, therefore, needed at an optimum level that minimizes building size in tandem with providing sufficient space to maintain functionality. For such design, architects and engineers need to be informed accurate and reliable space-use information. We present in this paper a conceptual framework of an agent-based space-use prediction simulation system that provides individual level space-use information over time in a building in consideration of project specific user information and activity schedules, space preference, ad beavioural rules. The information will accordingly assist architects and engineers to optimize space of the building as appropriate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.169-175
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• 2015

In the field of health informatics converging ICT technology and medicine technology, XML-based CCR document make sure the continuity and mobility of the information of patients. When a number of clients access CCR documents, wireless data broadcast that supports any number of clients can be an alternative for the scalability. In this paper, we propose a framework for wireless data broadcast of XML-based CCR documents. We design and implement the framework that can adopt various data scheduling algorithms and indexing schemes for the optimized performances of clients. The implemented framework shows the efficiency with simulations adopting various data scheduling algorithms and indexing schemes.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.103-109
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• 2018

This paper presents an idea and framework to automate a full cycle business process management and re-engineering by integrating traditional business process management systems, process mining, data mining, machine learning, and simulation. We build our framework on the cloud-based platform such that various data sources can be incorporated. We design our systems to be extensible so that not only beneficial for practitioners of BPM, but also for researchers. Our framework can be used as a test bed for researchers without the complication of system integration. The automation of redesigning phase and selecting a baseline process model for deployment are the two main contributions of this study. In the redesigning phase, we deal with both the analysis of the existing process model and what-if analysis on how to improve the process at the same time, Additionally, improving a business process can be applied in a case by case basis that needs a lot of trial and error and huge data. In selecting the baseline process model, we need to compare many probable routes of business execution and calculate the most efficient one in respect to production cost and execution time. We also discuss the challenges and limitation of the framework, including the systems adoptability, technical difficulties and human factors.

• Smart Structures and Systems
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• v.32 no.1
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.1129-1143
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• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.808-813
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• 2003

Maintaining agility and responsiveness m designing and manufacturing activities are the key issues for manufacturing companies to cope with global competition. Distributed design and control systems are regarded as an efficient solution for agility and responsiveness. However, distributed nature of a manufacturing system complicates production activities such as design, simulation, scheduling, and execution control. Especially, existing simulation systems have limited external integration capabilities, which make it difficult to implement complex control mechanisms for the distributed manufacturing systems. Moreover, integration and coupling of heterogeneous components and models are commonly required for the simulation of complex distributed systems. In this paper, a collaborative and adaptive simulation architecture is proposed as an open framework for simulation and analysis of the distributed manufacturing enterprises. By incorporating agents with their distributed characteristics of autonomy, intelligence, and goal-driven behavior, the proposed agent-based simulation architecture can be easily adapted to support the agile and distributed manufacturing systems. The architecture supports the coordination and cooperation relations, and provides a communication middleware among the participants in simulation.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.423-428
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• 1995

Simulation models have been developed to predict the overall behavior of the CANDU plant systems during normal operational transients. For real time simulation purpose, simplified thermal hydraulic models are applied with appropriate system control logics, which include primary heat transport system solver with its component models and secondary side system models. The secondary side models are mainly used to provide boundary conditions for primary system calculation and to accomodate plant power control logics. Also, for the effective use of simulation package, hardware oriented basic simulation network has been established with appropriate graphic display system. Through validation with typical plant power maneuvering cases using proven plant performance analysis computer code, the present simulation package shows reasonable capability in the prediction of the dynamic behavior of plant variables during operational transients of CANDU plant, which means that this simulation tool can be utilized as a basic framework for full scope simulation network through further improvements.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.5 s.149
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• pp.619-629
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• 2006

The safety assessment of the structure related to people has become the most important part in the process of the design. Especially, in the case of a ship, as regulations about the safety of passengers and the pollution in the ocean are strictly reinforcing, the safety assessment has become the most important part in the process of the design. In this paper, we suggested network-based simulation system framework using HLA (High Level Architecture) among many kind of simulations to assess the safety of the ship. In addition, the visualization method which is composed of graphic user interface for ship modeling and the visualization of ship motion is presented.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.6
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• pp.542-553
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• 2020

Virtual world and simulation need large scale map rendering. However, rendering too many vertices is a computationally complex and time-consuming process. Some game development companies have developed 3D LOD objects for high-speed rendering based on distance between camera and 3D object. Terrain physics simulation researchers need a way to recognize the original object shape from 3D LOD objects. In this paper, we proposed simply automatic LOD framework using point cloud data (PCD). This PCD was created using a 6-direct orthographic ray. Various experiments are performed to validate the effectiveness of the proposed method. We hope the proposed automatic LOD generation framework can play an important role in game development and terrain physic simulation.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.226-228
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• 2006

In this paper we describe a simulation and development framework for designing mobile 3D graphics architectures. We are developing a simple and flexible simulation and verification environment (SVE) that uses gITrace's ability to intercept and redirect an OpenGL/ES streams. In combination wlth gITrace to trace OpenGL/ES commands, the SVE simulates the behavior of mobile 3D graphics pipeline during playback of traces, and then produces the second geometry trace that can be used as a test vector for the Verilog/HDL RT-level model. By comparing the frame-by-frame results, we can conduct architectural verification. To demonstrate the functionality of the SVE, we show the implementation of the verified mobile 3D architecture on a FPGA board. For this, we also present an application development environment (ADE) includes a mobile graphics API and a device driver interface (DDI). The proposed two software environments, the SVE and the ADE could be used fer developing and testing mobile applications, architectural study and speculative hardware designs.